IBM is a well-known company in the tech industry, and it has launched a Deep Learning as a Service (DLaaS).

Using this, IBM aims to help AI developers, by allowing them to train their neural networks using popular frameworks such as TensorFlow, PyTorch, and Caffe, without having to buy and maintain the needed hardware themselves.

Each cloud processing unit is meant to be easy to set up and prepare. Here users can create their own Deep learning networks without the need for infrastructure management from users. And also because it runs in the cloud as a service, they only pay for the resources they need, paying only for GPU time.

The enhancements live within Watson Studio, and this DLaaS should be convenient for developers and also data scientists.

To use the service, users just have to prepare their data and upload them to IBM.

Using IBM's DLaaS, users can choose from a list of supported deep learning frameworks, a neural network model, Training data and cost constraints. They can then begin training their AI, with the service taking care of the rest. Users can download the training results after it finishes.

Deep neural network training is computationally intensive. It requires a system with the right combination of software, drivers, compute, memory, network, and storage resources.

"To realize the full potential of this rising trend, we want this technology to be more easily accessible to developers and data scientists so they can focus more on doing what they do best," said IBM on its blog post.

This DLaaS also runs on its Watson platform. And because IBM's DLaaS solution allows developers to have access to hardware that is expensive to small companies with limited budget, here, IBM lowering the barrier to entry for all users, not just a few experts.

This is an evidence that AI will indeed infiltrate every other industry at any level of businesses.